Understanding hydrological trends by combining the Budyko hypothesis and a stochastic soil moisture model

2014 ◽  
Vol 60 (1) ◽  
pp. 145-155 ◽  
Author(s):  
Zhentao Cong ◽  
Xiaoying Zhang ◽  
Dan Li ◽  
Hanbo Yang ◽  
Dawen Yang
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Model

scholarly journals CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project

2021 ◽  
Author(s):  
Binghao Jia ◽  
Longhuan Wang ◽  
Yan Wang ◽  
Ruichao Li ◽  
Xin Luo ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Grid Point ◽  
Global Ocean ◽  
Surface Model ◽  
Past Century ◽  
Model Intercomparison ◽  
Soil Moisture Model ◽  
Surface Snow ◽  
Intercomparison Project

AbstractThe datasets of the five Land-offline Model Intercomparison Project (LMIP) experiments using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) of CAS Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3 (CAS FGOALS-g3) are presented in this study. These experiments were forced by five global meteorological forcing datasets, which contributed to the framework of the Land Surface Snow and Soil Moisture Model Intercomparison Project (LS3MIP) of CMIP6. These datasets have been released on the Earth System Grid Federation node. In this paper, the basic descriptions of the CAS-LSM and the five LMIP experiments are shown. The performance of the soil moisture, snow, and land-atmosphere energy fluxes was preliminarily validated using satellite-based observations. Results show that their mean states, spatial patterns, and seasonal variations can be reproduced well by the five LMIP simulations. It suggests that these datasets can be used to investigate the evolutionary mechanisms of the global water and energy cycles during the past century.

scholarly journals Modelling soil moisture for a grassland and a woodland site in south-east England

2002 ◽  
Vol 6 (1) ◽  
pp. 39-48 ◽  
Author(s):  
E. Blyth
Keyword(s):  
Soil Moisture ◽  
Prediction Models ◽  
Meteorological Data ◽  
Field Capacity ◽  
Runoff Generation ◽  
Surface Exchange ◽  
Soil Moisture Model ◽  
Meteorological Observations ◽  
The Uk ◽  
Grassland Site

Abstract. This paper describes a comparison between two soil moisture prediction models. One is MORECS (Met Office Rainfall and Evaporation Calculation Scheme), the Met Office soil moisture model that is used by agriculture, flood modellers and weather forecasters to initialise their models. The other is MOSES (Met Office Surface Exchange Scheme), modified with a runoff generation module. The models are made compatible by increasing the vegetation information available to MOSES. Both models were run with standard parameters and were driven using meteorological observations at Wallingford (1995-1997). Detailed soil moisture measurements were available at a grassland site and a woodland site in this area. The comparison between the models and the observed soil moisture indicated that, for the grassland site, MORECS dried out too quickly in the spring and, for the woodland site, was too wet. Overall, the performance of MOSES was superior. The soil moisture predicted by the new, modified MOSES will be included as a product of Nimrod - the 5 km x 5km gridded network of observed meteorological data across the UK. Keywords: Soil moisture, model, observation, field capacity

Hydrologic soil properties and application of a soil moisture model in a balsam fir forest

1988 ◽  
Vol 18 (4) ◽  
pp. 427-434 ◽  
Author(s):  
Richard Barry ◽  
André P. Plamondon ◽  
Jean Stein
Keyword(s):  
Soil Moisture ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Crop Coefficient ◽  
Balsam Fir ◽  
Physical Parameters ◽  
Volumetric Soil Water Content ◽  
Soil Moisture Model

An analysis of hydrologic soil properties and the prediction of volumetric soil water content during four summers have been done for a site located in the balsam fir (Abiesbalsamea (L.) Mill.) forest of the Lac Laflamme watershed. The hydrologic properties were used to identify three different soil layers, THIRSTY, a soil moisture model using the Penman evapotranspiration formula, was applied to predict daily volumetric water content of these layers. Predictions of soil moisture with the calibrated model were close to the observed data for the median layer (20–60 cm from the soil surface) and less accurate for the surface layer (0–20 cm) where important transpiration activities take place. The model appeared unreliable for predicting soil water content of the bottom layer (60–100 cm) which was often saturated by groundwater. The calibration of the model required modifications of the observed values of the available water content at field capacity and the relative root density factor and was adjusted with the crop coefficient of the Penman evapotranspiration formula. These modifications of observed physical parameters raise the question of the feasibility of extrapolating the model to other sites without extensive calibration. The high sensitivity to variations of the crop coefficient applied to the evapotranspiration equation indicated that a more physically based transpiration model, supported by field-oriented process studies, would be required to improve the model's performance.

Neural network soil moisture model for irrigation scheduling

2021 ◽  
Vol 180 ◽  
pp. 105801
Author(s):  
Zhe Gu ◽  
Tingting Zhu ◽  
Xiyun Jiao ◽  
Junzeng Xu ◽  
Zhiming Qi
Keyword(s):  
Neural Network ◽  
Soil Moisture ◽  
Irrigation Scheduling ◽  
Soil Moisture Model

Soil moisture modelling — conception and evolution of the VSMB

1996 ◽  
Vol 76 (3) ◽  
pp. 251-261 ◽  
Author(s):  
Wolfgang Baier ◽  
Geo. W. Robertson
Keyword(s):  
Soil Moisture ◽  
Support Staff ◽  
The Other ◽  
Concept Design ◽  
Highly Qualified ◽  
Plant Research Institute ◽  
Department Of Agriculture ◽  
Climatological Data ◽  
Soil Moisture Model ◽  
Soil Moisture Budget

The Versatile Soil Moisture Budget (VSMB), including the background leading to its development in the "early days" meaning around 30 yr ago, is described. National and international efforts before that time created a healthy climate for the development of agrometeorology in Canada and the pioneering work in soil moisture and crop-weather modelling.Events in the early days leading to a concerted endeavour of soil moisture modelling included: (i) a small group of highly qualified professionals from different disciplines, as well as support staff, had been established under the guidance of a team leader at the then Plant Research Institute (PRI); ii) a Canada wide crop-weather study had produced daily climatological and crop data at nine Canada Department of Agriculture establishments over 10 yr (1953–1962); iii) a computer became available to PRI staff (IBM 1620 with 16K); and (v) several sub-models providing the necessary input to the soil moisture model were at various stages of development (e.g. the "latent" evaporation and the biometeorological time scale sub-models).This paper presents an overview of the development of the VSMB using standard climatological data for generating daily soil moisture estimates under crops. Its concept, design and widespread applications in Canada and abroad are discussed. A more detailed analysis is left to the other presentations at this Symposium. Key words: Soil moisture, modelling, applications

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